Software Development Engineer Intern
Bidart, Nouvelle-Aquitaine, France
SOPHiA GENETICS
We help generate insights from digital health data to improve scientific outcomes.This position is in partnership with the ESTIA School, located in Bidart. Only applicants from this institution will be reviewed and considered for the position.
Complete an internship project at SOPHiA GENETICS whose mission is to build the future of AI-assisted medicine, joining the Genomic Workflow Enhancement as a Software Development Engineer Intern.
Your mission:
Help us make the most of our distributed system’s resources by working closely with our "executor" component. The executor is a key part of our system, turning data scientists' code (called "pipelines") into tasks that run smoothly across many machines. As an intern, you’ll help build machine learning models to smartly allocate resources, improve system performance, and lower costs.
This project could make a big difference! By improving how we allocate resources, we aim to speed up pipeline execution and lower infrastructure costs, creating a more efficient and affordable system for managing large data pipelines.
You’ll be involved in:
- Resource analysis: checking how resources are currently used in our system, with a focus on the executor component.
- Machine learning integration: helping develop and use machine learning models to make task scheduling and resource use more efficient.
- Metrics integration: adding new metrics, like CPU and disk usage, to improve how we manage resources.
- Cost and performance optimization: adjusting our models to help tasks finish faster and lower costs.
Requirements
- Experience in working with Python.
- Familiarity with data analysis and interpretation.
- Familiarity with basic machine learning techniques and workflow.
- Strong communication skills in English, both written and verbal.
- Ability to work effectively in a collaborative team environment while being autonomous in task management.
- Motivation to learn and continuously improve.
- Strong problem-solving mindset and adaptability to complex, real-world challenges.
Benefits
What you will learn:
- Gaining hands-on experience in developing machine learning models for resource optimization in a large-scale distributed system.
- Understanding how to integrate machine learning models into operational systems for optimizing performance and reducing costs.
- Learning to analyze and manage resources in a distributed computing environment, focusing on the integration of additional metrics like CPU and disk usage.
- Developing practical experience in optimization and performance enhancement within a real-world infrastructure.
Location: Bidart, France
University Partner: ESTIA Students – Applications will be given priority as part of the partnership between SOPHiA GENETICS and ESTIA.
Start: March 2025
Contract type: 6-month internship
All SOPHiA GENETICS internships & apprenticeships are paid as per each country's best practices and degree level.
Application process
Apply now with your CV and any supporting information.
Suitably qualified candidates will be invited through an interview and screening process where you will speak with members of our Talent Acquisition Team, the hiring leader, alongside key colleagues, and stakeholders from across the business.
As a global business, English is our primary language and English-only speakers will be involved in your recruitment process. All resumes should be in English for a successful review!
SOPHiA GENETICS:
We believe there is a smarter, more data-driven way to make decisions in healthcare and our AI SaaS Platform enables that. You will have direct input into our mission to radically improve the outcomes for Cancer & Rare Disease patients globally. Enable our customers to push industry boundaries, as we pioneer into newly discovered fields and combine complex, multi-modal data for the first time!
For more information, visit our website: https://www.sophiagenetics.com/
Tags: Data analysis Data pipelines Machine Learning ML models Pipelines Python
Perks/benefits: Career development Startup environment
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